Speaker Introduction:

Camille Crittenden, Deputy Director of Citrus, introduces Jaron Lanier as a computer scientist, composer, visual artist, and author. Lanier is recognized for his pioneering work in virtual reality, a term he coined in the 1980s. He has received multiple awards and honors, including being named to Time 100 in 2010.

Entrepreneurial Ventures:

Lanier has co-created startups that were later absorbed by major tech companies such as Oracle, Adobe, and Google, underlining his impact in the technology sector.

Musical Background:

In addition to his technology-related work, Lanier is also noted for his contributions to music. He writes orchestral, chamber music, and film scores, and has performed with diverse musicians including Yoko Ono and Philip Glass.

Books and Thought Leadership:

Lanier has authored significant books like “You Are Not a Gadget” and “Who Owns the Future?”. George Dyson, another notable author, highlights that Lanier’s latest book offers critiques and solutions for the digital economy.

Lecture Topic:

The talk that Lanier is set to give is titled “How Can We Prevent Information Technology from Destroying the Middle Class?” This suggests that Lanier will offer perspectives that challenge conventional wisdom about the impact of technology, aligning with Citrus’s aim to present contrary and provocative views.

Personal Connection:

Jaron Lanier mentions that he resides in Berkeley, creating a personal connection with the audience. He expresses a desire for a less formal setting, considering sitting down to make the presentation more intimate.

This segment serves as an introduction to a lecture by Jaron Lanier, highlighting his multifaceted career, thought leadership, and the controversial yet insightful topic he is set to discuss.

Early Idealism:

Jaron Lanier recounts his experiences in the late ’70s and early ’80s, as part of a community that was captivated by the notion that computation and free information could revolutionize the world. This community was an amalgamation of libertarian and left-leaning individuals who believed that an open information system could counterbalance the centralization of power and make the world a better place.

Birth of Internet Economy:

Lanier discusses how the area just north of Berkeley’s campus was a breeding ground for the ideologies and designs that shaped today’s internet economy. However, he also mentions that there were influential contributions from other places like Palo Alto, MIT, and Wall Street.

Power Dynamics in Free Information:

Lanier points out that the idea of free and open information does not necessarily lead to equity. The reason is that those with the biggest and most effective computational resources reap more benefits from this freely available information. He ties this insight back to early manifestations on Wall Street, leading to market phenomena like the flash crash of 1987.

Warnings from History:

He discusses a significant event, the failure of Long-Term Capital Management in the 1990s. This venture, backed by Nobel laureates, aimed to use big data to extract money efficiently from financial markets. However, it eventually failed and needed a costly public bailout, the ramifications of which, Lanier argues, society is still paying for. This failure was an early indication of the flaws in the “information should be free” model, blinded by initial successes.

Changing Perspectives:

By the turn of the century, Lanier started to become concerned about the pervasive ideology he had once been a part of. He cites examples like Enron and suggests that while the idea of free information still has merit, the capitalist elements blended into the ideology have led to unforeseen consequences.

Overall, Lanier’s discussion reveals a journey from idealism to skepticism, raising cautionary points about the unintended consequences of free and open information when coupled with capitalism.

Personal History & Tech Ideals:

Jaron Lanier speaks about his early involvement in the tech community during the late 70s and early 80s. This period was marked by optimism and the belief that computational technology could bring about social and economic good. The ethos of the time was a mixture of libertarian and left-wing ideals, advocating for free information and computational opportunities.

The Problem with Power:

Lanier explains that the initial idea was to create open information systems that would prevent power consolidation by decentralizing communication channels. He reflects that this is still a valid and compelling idea, but problems have emerged as these concepts were applied in real-world scenarios.

Capitalism and Computation:

Alongside the open information ethos, there was a capitalist element that computation would become a new industry. Lanier notes that this has largely been successful, but it has also led to challenges.

Issues with Equity:

Lanier points out that the notion of “information should be free” doesn’t create equity. Those with larger or more effective computing capabilities benefit more from free information than others, as seen with Wall Street’s early use of computation.

The Turn of the Century: Enron:

Around the turn of the century, Lanier started to become concerned. Companies like Enron knowingly exploited computational capabilities for their benefit, with dire consequences for the public. Lanier says that investors learned the wrong lessons from earlier events like long-term capital, leading to problems such as Enron.

Decline of the Music Industry:

Lanier was initially an advocate of the idea that musicians should give away their music for free, thinking it would create more opportunities. However, this belief led to the decline of the music industry, resulting in a significant reduction in the number of financially successful musicians. The theory sounded great, but the empirical evidence showed otherwise.

Empirical Reality:

Lanier concludes that despite the initial high ideals, the real-world results have forced him to reassess his beliefs. Events like Enron and the decline of the music industry made him realize the importance of respecting empirical outcomes over theoretical ideals.

Technology’s Societal Impact:

Jaron Lanier emphasizes that while he is strongly pro-technology, he criticizes the current architectures in information technology for failing to strengthen the middle class and the economy. He argues that framing the discussion as ‘technology being good or bad’ is counterproductive; instead, focus should be on how we design these technologies.

More Than One Approach:

Lanier explains that there is more than one way to implement technology, especially information technology. The way we choose to design and use technology will largely influence its societal impacts, and this gives us options and responsibilities in terms of architecture and design.

Thought Experiment: Maxwell’s Demon:

Lanier introduces a thought experiment known as Maxwell’s Demon, an imaginary character from 19th-century physics. This ‘demon’ attempts to create perpetual motion by sorting molecules into hot and cold vats to generate energy. However, the experiment demonstrates that you always spend more energy running the system than you can gain from it, echoing a fundamental principle in thermodynamics known as “no free lunch.”

Information Processing as Real Work:

Drawing parallels from Maxwell’s Demon, Lanier points out that information processing itself constitutes real work in the physical sense. For instance, the mere act of storing information about the movement of a molecule requires energy. This means that computation has an actual physical effect, and thus an environmental impact, emphasizing that there are limits to how efficient these processes can be.

Challenging Illusions of Perpetual Gain:

The Maxwell’s Demon experiment serves as a metaphor for current technology systems that promise endless benefits but fail to deliver in the long run. Just like the perpetual motion machines that appear effective but eventually fail, technology also has its limitations and costs, which need to be critically evaluated.

This summary captures Lanier’s nuanced view on technology, emphasizing the need for thoughtful design and the limitations imposed by physical and economic realities.

Transition to the 90s:

Jaron Lanier takes the audience back to the early 90s when Wall Street first started using big data and computing power to automate profit-making through statistical methods.

Insurance Industry Epiphany:

Lanier recounts his experience at a planning retreat for the U.S. health insurance industry, where the CEO of a large health insurance company had an epiphany. Thanks to advancements in computing power, the CEO realized they could grow profits by insuring fewer people rather than more. By creating detailed profiles on individuals and using statistical correlations, the company could identify high-risk individuals and choose not to insure them.

Role of Big Data in Policy and Economy:

Lanier points out that this shift—using big data to serve fewer people and still make profits—is not just an industry trend but a fundamental issue affecting governance and the economy. This paradigm has led to crises like the government shutdown and potential credit defaults.

Maxwell’s Demon Analogy:

He draws an analogy to Maxwell’s demon, a theoretical construct that sorts particles based on temperature to maximize efficiency. The CEO wanted to be like Maxwell’s demon but with people, sorting them into high-risk and low-risk categories to maximize profit.

Critique of Big Data’s Illusion:

Lanier critiques this reliance on big data and statistical calculations to create ‘automatic profit machines’ or ‘security machines.’ He argues that it’s a dangerous illusion because it fails to recognize that economic systems, like any causal systems, cannot be optimized into perfection indefinitely.

Final Thoughts:

In essence, Lanier argues that the seemingly automatic optimization offered by big data is a fallacy that can have dire consequences on a broader scale, affecting not just industries but the overall socio-economic structure.

19th Century Technological Anxiety:

Jaron Lanier discusses how the 19th century was a time fraught with anxiety over the possibility that technology would render humans obsolete. He notes that the period was in many ways more futuristic than the 20th century, and was marked by significant societal shifts due to technology.

The Luddite Riots:

Lanier delves into the Luddite riots, which were reactions from textile workers in London against advancing manufacturing technologies. Initially violent, these riots were suppressed through public hangings. The Luddite movement became a symbol for those concerned about the social implications of technology.

Karl Marx’s Early Thoughts:

Lanier introduces Karl Marx as an early technology writer who pondered the fate of humans as machines became more advanced. Marx was concerned with how improvements in technology might distribute benefits. Specifically, Marx wondered whether a handful of people would gain while the rest suffered, or if the wealth and benefits would be more evenly distributed.

Marx’s Relevance Today:

Lanier notes that Marx’s early writings sound eerily contemporary, almost resembling the language of modern tech startups. Although Marx was concerned about the socio-economic impacts, he was also enthralled by the prospects of rapidly advancing technology.

Critique of Marx’s Solutions:

Lanier believes that Marx’s solutions for addressing the imbalance, such as centralized committees for wealth distribution, have been empirically discredited. He argues that such systems tend to concentrate too much power and consequently become corrupt and cruel.

In sum, Lanier explores how historical anxieties about technology’s impact on human life are not only relevant but also echoed in contemporary discussions. He critically engages with Marx’s early ideas, noting both their current applicability and their flawed solutions.

Ballad of John Henry:

Jaron Lanier discusses the Ballad of John Henry, a 19th-century folk song about a man who competes with a machine to lay down railroad tracks. John Henry wins but dies from exhaustion, symbolizing the human struggle against technological obsolescence.

Emergence of Science Fiction:

Lanier points out that the 19th century also gave birth to science fiction, a genre often centered around the theme of human obsolescence due to technology or superior aliens. This genre typically features a human hero who uses their innate “humanness” to overcome technology’s threat.

Modern Retellings:

According to Lanier, movies like “The Terminator,” “The Matrix,” and series like “Battlestar Galactica” are modern takes on this 19th-century theme. These stories often depict humans fighting back against technology or machines designed to make them obsolete.

H.G. Wells’ The Time Machine:

Lanier cites H.G. Wells’ “The Time Machine” as an early narrative that encapsulates fears of a divided human future. In this story, humanity splits into two groups: one that controls the machines and another that is farmed for food, illustrating a dystopian outcome.

E.M. Forster’s The Machine Stops:

Lanier recommends E.M. Forster’s short story “The Machine Stops,” written in the early 20th century. The story remarkably predicts elements of the internet, social media platforms like Facebook, and the concept of hacking. Forster wrote this as a counterpoint to H.G. Wells, whom he viewed as too focused on the technical aspects.

19th Century’s Influence on Today:

Lanier concludes that many cultural attitudes and artistic themes regarding the relationship between humans and technology originated in the 19th century. This period essentially laid the groundwork for our current discussions on how advancing technologies might render human roles obsolete.

In summary, Lanier articulates how the 19th century was a fertile ground for cultural and artistic explorations into the human anxiety surrounding technological obsolescence, themes that continue to resonate in modern times.

Transition to 20th Century:

Jaron Lanier discusses the transition from the 19th to the 20th century, noting how the mid-20th century brought relative prosperity and security in the developed world. He questions how this transformation occurred and why the fears of obsolescence from the 19th century did not materialize.

Creative Destruction:

Lanier explains the concept of “creative destruction,” which suggests that technological advancements that eliminate certain jobs also create new and better roles. He clarifies that this wasn’t automatic and required effort to achieve.

Labor Movement:

Lanier emphasizes the labor movement’s role in shaping the 20th century. Using the example of the car and truck industry, he illustrates how the labor movement gave workers in non-specialized jobs the ability to negotiate fair wages, preventing a race to the bottom.

Cooperation Between Labor and Management:

Interestingly, Lanier notes that there was a secret channel of cooperation between labor and management. Industrialists needed a middle class to serve as a customer base for their products, which led to them supporting fair wages for their workers.

Industrialists’ Realization:

Lanier discusses Henry Ford’s realization that to expand his business, he needed to pay his factory workers enough to afford the cars they were building. This approach forced competitors and suppliers to do the same, thereby creating a customer class necessary for market capitalism.

Abstraction and Future Implications:

Towards the end, Lanier introduces the concept of abstraction as a way to reduce the problem space when considering how information technology relates to society, suggesting that the lessons learned in the 20th century could inform future interactions between society and technology.

The Role of Middle Class:

Jaron Lanier emphasizes the critical importance of having a strong middle class in any society, regardless of ideological leanings. A strong middle class is seen as vital to the health of democratic systems, market economies, and the social fabric.

Corruption and Ruin:

Lanier argues that without a balanced distribution of wealth and a strong middle class, politics becomes corrupt, markets are ruined, and social systems degrade into caste-like structures. He highlights the negative consequences of wealth concentrating among a small elite group, stating that it undermines democracy, markets, and society at large.

Reframing Ideological Debates:

According to Lanier, the conversation should not be mired in left-right ideological debates, which he finds “tiresome,” “hopeless,” and “useless.” Instead, he suggests focusing on achieving a “sustainable distribution of outcomes” within society, sidestepping traditional ideological arguments.

Mathematical Perspective:

Lanier encourages thinking about the issue in terms of statistics and normal distribution. He argues that an “honest” measurement of contributions within an economy should result in a normal distribution of outcomes. When this doesn’t happen, it’s an indication that something in the system is flawed.

Sustainability of Distribution:

Lastly, Lanier hints at a more detailed argument for why deviations from a normal distribution are unsustainable but doesn’t elaborate in this segment. He leaves the audience with the idea that aiming for a normal distribution of wealth and resources would make ideological debates less relevant.

20th Century Mechanisms:

Jaron Lanier discusses how the 20th century had various “ad hoc” mechanisms to create a more balanced, albeit artificial, distribution of wealth and opportunities. These schemes included things like taxi medallions, union memberships, and tenure in academia. Lanier refers to these as “levies,” describing them as small dams that hold up capital for certain groups of people.

The Shift in the 21st Century:

Lanier notes a significant shift with the advent of big computing and big data. Businesses are no longer interested in a broad customer base but focus on a smaller, more profitable set of customers. This is a move from an inclusive to an excluding form of capitalism.

The Seduction of Big Data:

The allure of big data lies in its ability to make precise projections. Lanier describes this as feeling like having the “Midas touch” and explains that even marginal advantages over competitors can lead to significant long-term benefits. It’s a “compound interest scheme,” which at first appears to be automatic money-making.

Shortcomings and Failures:

However, Lanier warns that the use of big data has its pitfalls. Because the world is not just a sequence of smoothly flowing data points, the models can hit “brick walls,” leading to catastrophic failures like financial crises. He criticizes the movement advocating for the “End of Theory,” which claims that big data can replace the need for deep understanding and theory.

Repeated Cycles:

Lanier concludes by saying we’re in a cycle of using big data for short-term gains, which will inevitably lead to long-term failures, requiring public bailouts. This cycle perpetuates as people are seduced by the initial rush of success, ignoring the potential for long-term catastrophe.

Early Adoption in Finance and Logistics:

Jaron Lanier discusses how the financial world quickly grasped the potential of optimizing data for gains. Notably, Walmart employed similar data optimization tactics to outperform competitors by improving its supply chain logistics. He highlights how the same mathematical and programming experts often worked in both sectors, demonstrating that data optimization transcends industry boundaries.

Intelligence Agencies and Late Silicon Valley:

Lanier remarks that intelligence agencies also realized the value of data optimization in the 1990s. In contrast, Silicon Valley was late to adopt this paradigm. During the 90s, Silicon Valley focused on empowering the middle class by selling personal computers that allowed individuals to own their data. This ownership enabled people to establish small businesses, fostering economic prosperity.

Shift in Data Ownership:

The speaker identifies a significant shift around the turn of the century when cloud services began to emerge. Storing data on a cloud service gradually tilts the advantage toward the service provider through a compound interest-like effect. He posits that whoever owns and controls the data gains the most advantage over time.

Concept of Siren Servers:

Lanier introduces the term “siren servers” to describe systems that exploit human weaknesses for data collection, much like the sirens in Homer’s epics seduced sailors to their doom. He argues that computers don’t inherently harm us; instead, it is our own lust and greed that can mislead us into detrimental actions.

Advertising in the New Age:

Finally, he observes a shift in the meaning of advertising within Silicon Valley. Whereas advertising had traditionally been a form of expression, in the data-centric world, it has taken on a more manipulative role. This new form of advertising capitalizes on constantly changing human habits, made possible by technological advancements.

Lanier concludes by urging the importance of speaking honestly about these developments, as he considers himself a part of the tech world he critiques.

Evolution of Advertising:

Jaron Lanier underscores a fundamental shift in the nature of advertising as executed by Silicon Valley companies. Unlike traditional advertising, which he describes as more persuasive and expressive, the new form is focused on micromanaging user behavior. Lanier argues that Silicon Valley’s approach to advertising aims to modify user behavior by leveraging limited screen options and tailored links.

Data-Driven Behavioral Models:

According to Lanier, companies compile behavioral models based on the data they collect from users to predict which stimuli will affect users and when. These predictive algorithms can nudge users into particular actions, like walking into a café when their phones show a friend recommending it. The algorithms don’t have to be perfect; they merely need to be slightly better than random selection.

The Question of Harm:

Lanier confronts the notion that this form of advertising is harmless. He contends that what may seem benign actually has broader implications. He highlights how Silicon Valley companies provide “free” information services like search engines and social networking platforms. These services are monetized through data-driven advertising, which, although seemingly harmless, manipulates user behavior.

Ownership and Contribution:

In a compelling argument, Lanier states that while companies offer these services as free, the data that powers them is provided by the users. Every “big data service is made of you,” he says, emphasizing that all data in computer networks is the result of human labor—be it setting up a sensor, typing information, or snapping a picture.

Conclusion:

Lanier cautions against considering this system harmless. The services we perceive as free are built on the aggregation of our own contributions and labor, reshaped into models that subtly manipulate our behaviors for corporate gains.

Translation as a Case Study:

Jaron Lanier discusses the example of online translation services to illustrate how seemingly “free” online services work. He notes that while it may seem like a fantastic deal for users, it’s important to recognize that these services are not generated by machine autonomy but are based on big data—essentially, a large corpus of human effort.

The Reality of Big Data:

Lanier emphasizes that whenever we hear “big data,” it really means a large group of people whose contributions are being made invisible. For instance, the translations provided by free online services are a rehash of real human translators’ work. Professionals in the field are finding it increasingly difficult to make a living despite their work being as essential as ever.

Unacknowledged Human Labor:

The speaker argues that not only translators but also musicians, legal researchers, and even healthcare professionals are affected. While technology is advancing, the core data often comes from human labor, which is being ignored or unpaid.

Two Sides to the Issue:

Lanier presents two perspectives on this issue. First is a class or Marxist perspective, where middle-class professionals are not getting their due because of the illusion of machine automation. Second is the economic side, where the illusion of ‘free’ services throws a significant part of the economy “off the books,” essentially causing the market to shrink.

Economic Growth vs Consolidation:

Lanier makes a case for economic growth being preferable to consolidation in a shrinking market. He argues that technological improvements should actually expand the economy, but the current model forces the economic benefits “off the books.” This dynamic puts pressure on the elites to consolidate resources and diminishes empathy in society.

The Vicious Cycle:

Lanier warns that the situation is not sustainable, and it’s a “terrible deal” for everyone involved. Both the disenfranchised workers and elites would benefit more from an expanding economy than from battling for a bigger share of a shrinking pie.

Honest Economic Growth:

Jaron Lanier advocates for a model of economic growth based on honest accounting of data and its value. This is neither a left nor right political argument, but rather an economic viewpoint that Lanier believes could help create a more equitable society.

Initial Ideas for Digital Networks:

Lanier refers to Ted Nelson, a Harvard student from 1960, who first proposed the idea of a digital architecture for connecting people. Nelson’s idea was built around a universal micropayment system, where every bit of data placed on the network would be tracked. Payments would flow back proportionally to individuals based on the usage of their data.

Complexity and Uncertainty:

While Lanier acknowledges the concept’s complexity and unanswered questions, he asserts that it deserves to be tested. He is exploring this in his new book but emphasizes that he cannot guarantee its success.

Value of Personal Data:

Lanier argues that the market value for individual data is rising and already holds significant worth, even for ‘the most boring person in the world.’ He suggests that the current value for an average person’s data could be in the hundreds to low thousands of dollars.

Societal Implications:

If the value of individual data hits the poverty line, Lanier sees a potential for new societal models that neither leave people to die in poverty nor rely on redistributive schemes. Through honest accounting of big data, a just and sustainable society could potentially be achieved without sacrificing technological advancement.

Reception Among Peers:

Lanier states that the reception of his ideas has been largely positive among his peers and Silicon Valley founders. He notes that those who are truly innovative remain open to new ideas and experimental mindsets, contrasting them with those who treat existing ideas as unchangeable orthodoxies.

Alternative Applications and Tests:

Lanier proposes testing his ideas in different domains, like 3D printing, where the designs could be shared with a similar micropayment structure. He believes it is crucial to explore whether such a system could create a more vibrant and equitable community.

Overall, Lanier’s talk focuses on the need for an honest economic model that fairly compensates individuals for their data, thereby potentially revolutionizing societal structures and fostering equitable growth.

Data Agency:

Jaron Lanier discusses the all-or-nothing choices people currently face concerning data privacy and agency. Navigating privacy settings is complex, and companies like Facebook may not even implement these settings reliably.

Valuation of Personal Data:

Lanier introduces an alternative where people could set the price of their own data. This would create a spectrum of choices between fully opting in or out of data schemes. It would balance the power between service providers and users, eliminating the mere data extraction practices by service providers.

Limits on Government:

Adding a monetary value to data would also limit government agencies like the NSA from unlimited data collection. Lanier suggests that an army of accountants could enforce this pricing, therefore setting limits on government power through financial constraints.

Academic Institutions and Online Education:

Lanier criticizes the current trend in academia of offering free Massive Open Online Courses (MOOCs). He argues that this undermines diversity in education and can ruin academic careers. Lanier distinguishes between making education “free” and making it “affordable,” advocating for the latter.

Music Industry’s Illusion:

Lanier discusses the illusion that many musicians are thriving by giving away their music online. He argues that the number of musicians who are actually successful in this model is extremely low. The glamorization of online success distorts the reality of financial struggles for most artists.

Network Architecture:

Lanier suggests that the architecture of a network determines the distribution of economic outcomes. Hub-and-spoke networks like YouTube lead to a few winners and many losers, which he finds problematic. He advocates for densely connected networks, where a more normal distribution of outcomes is likely.

Lanier’s discussion offers a critical look at current practices and suggests alternatives that offer more agency to individuals in how their data is used and valued.